Spatial-temporal distribution of extreme rainfall thresholds and assessment of urban waterlogging impact during flood seasons in Shanghai
The intensification of extreme rainfall events during flood seasons poses a significant threat of urban waterlogging in cities.This study focuses on assessing the impact of extreme rainfall on urban waterlogging,particularly during flood seasons in Shanghai,China.Utilizing nearly three decades of daily rainfall data,we established a time series of daily extreme rainfall thresholds and categorized rainfall periods into three distinct phases including Meiyu,midsummer,and autumn rain periods,and the difference in the classification passes the statistical tests.The analysis of extreme rainfall threshold scenarios revealed that peak rainfall occurs during the midsummer period,with spatial distribution patterns closely linked to urbanization levels across city centers and suburbs,as well as temporal variations during the flood season.Employing the Mike21 numerical model,we constructed an urban waterlogging model to simulate extreme rainfall scenarios during flood seasons.Results indicate that for threshold scenarios at the 90th,95th,and 99th percentiles,suburban areas exhibit the highest proportion of inundation.Conversely during the midsummer period,inundation is predominantly concentrated on the central urban and southeastern regions of Shanghai,with the maximum water depth up to 1.5 m.Additionally,the results of 99th percentile scenario of high exposure to waterlogging(with inundation depth>0.15 m)indicate that roads are the highest exposure,with inundation rates exceeding 22%.Buildings follow closely,with inundation rates surpassing 8%,while agricultural land experiences comparatively lower inundation rates,exceeding 4%.The results underscore the importance of prioritizing measures to mitigate extreme rainfall events,particularly those exceeding the 99th percentile during flood seasons.By providing decision support grounded in empirical data and advanced modeling techniques,the results contribute to enhancing pluvial flood prevention and mitigation strategies to local government.
flood season rainfallrainfall thresholdurban waterloggingexposure of elements at risk
NETL
NSTL
万方数据
